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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Ministral 3 14B 2512Mistral AIRemove
  2. DeepSeek V4.1 FlashDeepSeekRemove
  3. GLM 5.3 FlashZ.AIRemove
  4. Hy4 previewTencentRemove

4 is the maximum. Remove one to add another.

ministral-14b-2512 vs deepseek-v4.1-flash vs glm-5.3-flash vs hy4-preview
AttributeMinistral 3 14B 2512ministral-14b-2512DeepSeek V4.1 Flashdeepseek-v4.1-flashGLM 5.3 Flashglm-5.3-flashHy4 previewhy4-preview
Pricing
Input$0.20 / 1M$0.30 / 1M$0.075 / 1M$0.834 / 1M
Output$0.20 / 1M$1.20 / 1M$0.25 / 1M$2.50 / 1M
Cache Write (5m)$0.20 / 1M$0.30 / 1M$0.075 / 1M$0.834 / 1M
Cache Write (1h)$0.20 / 1M$0.30 / 1M$0.075 / 1M$0.834 / 1M
Cache Read$0.20 / 1M$0.30 / 1M$0.075 / 1M$0.834 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context262.1K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderMistral AIDeepSeekZ.AITencent
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryMinistral 3 14B is the largest model in the Ministral 3 lineup, delivering near–frontier performance similar to the larger Mistral Small 3.2 24B. It's a powerful yet efficient language model that also includes vision capabilities.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows.